maildoc
maildoc
轻量级电子邮件搜索、附件检索和 PDF 提取工具,适用于 AI 智能体和自动化。
设置
pip install -r requirements.txt在 .env 中设置凭据(参见 .env.example):
GMAIL_USERNAME=user@example.com
GMAIL_APP_PASSWORD=your_app_password快速开始
from maildoc import search_emails, download_attachment, extract_pdf_text
# Search emails with attachments
emails = search_emails(
sender="billing@example.com",
with_attachments=True,
limit=5,
)
# Download and extract text from PDF attachments (with optional password for protected files)
for email in emails:
for att in email["attachments"]:
if att["filename"].endswith(".pdf"):
pdf_bytes = download_attachment(email["uid"], att["filename"])
if pdf_bytes:
# Pass password if the PDF is password-protected (e.g., bank statements)
text = extract_pdf_text(pdf_bytes, password="optional_password")
print(text)MCP 服务器(Claude Desktop / Cursor / Antigravity)
作为 Model Context Protocol (MCP) 服务器运行:
python server.py示例 claude_desktop_config.json:
{
"mcpServers": {
"maildoc": {
"command": "python",
"args": ["/absolute/path/to/maildoc/server.py"],
"env": {
"GMAIL_USERNAME": "user@example.com",
"GMAIL_APP_PASSWORD": "your_app_password"
}
}
}
}工具参考
电子邮件与搜索
search_emails(sender, subject, body, seen, date_gte, date_lt, with_attachments, folder, limit):搜索邮箱并返回结构化字典。fetch_email_by_uid(uid, folder):按 UID 获取单个电子邮件。list_folders():列出邮箱文件夹。mark_email_as_read(uid, folder):将电子邮件标记为已读。move_email(uid, destination_folder, source_folder):在文件夹之间移动电子邮件。delete_email(uid, folder):删除电子邮件。create_folder(folder_name):创建邮箱文件夹。delete_folder(folder_name):删除邮箱文件夹。connect_to_email()、disconnect_from_email():连接生命周期辅助函数。
PDF 提取
read_pdf_attachment(uid, attachment_filename, password=None, folder="INBOX"):下载附件并直接一步提取其文本(非常适合 MCP / AI 智能体)。extract_pdf_text(pdf_bytes, password=None):从 PDF 字节中提取全部文本。extract_pdf_page_text(pdf_bytes, page_number, password=None):从特定页面(从 1 开始索引)提取文本。
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